{"uid":"cap_ePOzRwZh_p6oP-P-1eObu","slug":"transport-ridership-record-quality-audit-string-normalisation-daily-4e64c9f2","name":"Transport Ridership — Record Quality Audit + String Normalisation + Daily Sum Series","description":"Transport ridership — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied transport ridership records (passenger_count, service_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-economics-05-198?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","passenger_count","service_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"service_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"passenger_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","service_count":1,"passenger_count":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","service_count":2,"passenger_count":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","service_count":3,"passenger_count":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","service_count":4,"passenger_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["passenger_count","service_count"],"type":"string","default":"passenger_count"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_J2F0YdrF1GpeJsx0i7I53","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs three local analytical reports on supplied transport ridership data: a record quality audit, string normalisation, and a daily sum time series for passenger or service counts.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and daily passenger_count sum series on my transit ridership data? I have up to 50 rows with fields row_id, region, date, passenger_count, and service_count — please analyse passenger_count.","exampleUseCases":[{"title":"Transit data quality check before reporting","prompt":"I've got a batch of 120 ridership records with row_id, region, date, passenger_count, and service_count. Can you audit them for quality issues, normalise the region strings, and give me a daily sum series for passenger_count before I send this to the board?"},{"title":"Daily service count aggregation for operations","prompt":"Can you take these 80 transit rows and produce a daily sum series for service_count, plus flag any record quality problems and normalise the region labels so they're consistent?"},{"title":"Cleaning messy ridership export from legacy system","prompt":"I exported ridership data from our old system — 150 rows with some nulls and inconsistent region names. Please run a quality audit, normalise the strings, and give me the daily totals for passenger_count so I can see what we're working with."}],"resultDescription":"Three reports returned together: (1) a record quality audit flagging missing values, out-of-range numbers, or malformed dates; (2) normalised string output for the region field; (3) a daily aggregated sum time series for either passenger_count or service_count, covering up to 200 input rows.","failureModes":["Exceeds 200 row limit — request rejected","Missing required fields (row_id, region, date, passenger_count, service_count) — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema rejection","Numeric values outside allowed range — validation error","Empty rows array — minItems constraint violation"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous local analytical reports on transport ridership data — quality audit, string normalisation, and daily sum series — in a single low-cost call. Ideal for pre-analysis data cleaning pipelines where you want to validate, clean, and aggregate ridership figures (passenger or service counts) without any external lookups or live data dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:25.109Z","isFirstParty":false,"canonicalSlug":"transport-ridership-record-quality-audit-string-normalisation-daily-4e64c9f2"}